• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.147-149
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• 2022

This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.7-12
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• 2022

This paper introduces the implementation of the AWS IoT service and MQTT based smart home system. The smart home system implemented in this study can monitor temperature and humidity, and can manually adjust the air conditioner heating, and can check the visitors with the camera and remotely control the door lock. The implemented smart home system controls door locks, heating and air conditioners using Arduino, and manages the collected data and control information using the AWS IoT service. In this study, the Android app has been developed to allow users to control IoT devices remotely, and the MQTT protocol was used for data communication and control between the app and the AWS IoT server and Arduino. The implemented smart home system has been implemented based on AWS IoT service, which has scalability to add sensors and devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.351-353
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• 2021

In recent years, while the demand for electricity is rapidly increasing, fire accidents due to negligence in management of switchboards. In particular, switchboards for industrial and electrical resource control can cause serious problems. Thus, for the safety management of power switchboard, a secondary response is conducted to control firing when a specific condition value is satisfied, but in this case, it is highly likely that a considerable amount of time has elapsed after firing. In this paper, we propose a method to acquire big data for the development of a switchboard temperature and power control system that can actively respond to the current situation by monitoring and learning the temperature of the switchboard's busbar connection in real time. Specifically, a method for periodically acquiring and managing data such as temperature and power from various scattered sensors is proposed.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.111-119
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• 2023

Internal storage state, weight data, and weight-centered calculation values for overhead bin can all be seen in this paper's real-time internal status identification system. The suggested system offers such valuable data via a range of sensors, including load cells and switch arrays. The proposed system could locate internal free space, locate the center of gravity, and give real-time visual information. It was developed utilizing an embedded system and the C programming language. These features led to the creation of smart overhead bins and real-time cargo loading monitoring technologies, both of which could one day aid in the creation of a cargo loading automation system.

• Smart Media Journal
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• v.12 no.5
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• pp.81-87
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• 2023

In this paper, accidents in high-voltage overhead distribution lines, which provide stable power supply in the power system, cause inconvenience in life and disruption of production of companies. 22.9 [kV] high-voltage overhead power distribution lines aim to improve reliability and stability, such as damage caused by rain, snow, wind, etc., or electric shock prevention. Therefore, in order to prevent wire disconnection accidents due to deterioration of electrical conductivity or tensile strength due to corrosion of overhead distribution lines, it is necessary to prevent unexpected accidents in the future through regular inspection and repair. In order to diagnose deterioration due to corrosion of distribution lines, a diagnostic system (measuring instrument) is installed on the wires to monitor the condition of the wires. The manager on the ground receives the measured data through ZigBee wireless communication, controls the diagnosis system through the diagnosis system program, and grasps the condition of the overhead distribution line through the measured data and photographed photos, and predicts the life of the wire along with the visual inspection method. developed a program.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.46-46
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• 2022

유기물의 복잡한 혼합물인 CDOM(Colored or Chromophoric Dissolved Organic Matter)은 하천 내 BOD(Biological Oxygen Demand), COD(Chemical Oxygen Demand) 및 유기 오염물질과 상당한 관련이 있다. CDOM은 가시광선 영역에서 빛을 흡수하는 성질을 가지고 있으며, 최근 원격감지 기술로 CDOM을 모니터링하기 위한 연구가 진행되고 있다. 본 연구에서는 백제보 상류 23km 구간에서 3년(2016~2018) 중 13일의 초분광영상을 활용하여 머신러닝 기반 CDOM을 추정 알고리즘을 개발하고자 한다. 초분광영상은 400~970 nm의 범위의 4 nm 간격 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 항공기 탑재 AsiaFENIX 초분광 센서를 통해 수집하였으며 CDOM은 Millipore polycarbonate filter (𝚽47, 0.2 ㎛)에서 여과된 CDOM 샘플 자료를 200~800 nm의 흡수계수 스펙트럼으로 추출하여 사용하였다. CDOM 값은 전체기간 동안 2.0~11.0 m^-1의 값 분포를 보였으며 5 m^-1이상의 고농도 구간 자료개수가 전체 153개 샘플자료 중 21개로 불균형하다. 따라서 ADASYN(Adaptive Synthesis Sampling Approach)의 oversampling 방법으로 생성된 합성 데이터를 사용하여 원본 데이터의 소수계층 데이터 불균형을 해결하고 모델 예측 성능을 개선하고자 하였다. 생성된 합성 데이터를 입력변수로 하여 ANN(Artificial Neural Netowk)을 활용한 CDOM 예측 알고리즘을 구축하였다. ADASYN 기법을 통한 합성 데이터는 관측된 데이터의 불균형을 해결하여 기계학습 모델의 CDOM 탐지 성능을 향상시킬 수 있으며, 저수지 내 유기 오염물질 관리를 위한 설계를 지원하는데 사용할 수 있을 것으로 판단된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.256-264
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• 2023

Smart farm technology using IoT is one of the technologies that can increase productivity and improve the quality of agricultural products in agriculture, which is facing difficulties due to the decline in rural population, lack of rural manpower due to aging, and increase in diseases and pests due to climate change. . Smart farms using existing IoT simply monitor farms, implement smart plant growers, and have automatic greenhouse opening and closing systems. This paper implements a smart farm system based on MQTT, an industry standard protocol for the Internet of Things, and Node-RED, a representative development middleware for the Internet of Things. First, data is extracted from Arduino sensors, and data is collected and transmitted from IoT devices using the MQTT protocol. Then, Node-RED is used to process MQTT messages and store the sensing data in real time in MongoDB, a representative NoSQL, to store the data. Through this smart farm system, farm managers can use a computer or mobile phone to check sensing information on the smart farm in real time, anytime, anywhere, without restrictions on time and space.

• Journal of Soil and Groundwater Environment
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• v.29 no.4
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• pp.1-11
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• 2024

This study evaluated a method for prompt and periodic monitoring of moisture content in the waste layer of a landfill using a Time Domain Reflectometry (TDR) sensor, aimed at ensuring the stable operation of the bioreactor facility at the 2nd landfill of the SUDOKWON Landfill Site. It was found that the TDR sensor is sensitive to variables such as temperature changes and ion content in both the waste layer and leachate, indicating that a correction equation is necessary. A correction equation derived through regression analysis demonstrated a high correlation (correlation coefficient = 0.9647), and field verification experiments confirmed its reliability with an average deviation of only 1.5%. This verifies that the TDR sensor is effective for measuring and monitoring moisture content in landfills. It is also anticipated to be useful for various applications, including monitoring leachate levels, detecting leachate leakage, and assessing rainwater infiltration.

• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.43-52
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• 2024

This paper presents an anomaly detection system that uses an LSTM-Autoencoder model to identify early-stage anomalies in the blade pitch system of floating wind turbines. The sensor data used in power plant monitoring systems is primarily composed of multivariate time-series data for each component. Comprising two unidirectional LSTM networks, the system skillfully uncovers long-term dependencies hidden within sequential time-series data. The autoencoder mechanism, learning solely from normal state data, effectively classifies abnormal states. Thus, by integrating these two networks, the system can proficiently detect anomalies. To confirm the effectiveness of the proposed framework, a real multivariate time-series dataset collected from a wind turbine model was employed. The LSTM-autoencoder model showed robust performance, achieving high classification accuracy.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.8
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• pp.462-467
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• 2009

Researches and developments on BEMS are performed world-widely through sustainable management in various conditions. However, there are many obstacles to adapt the system in existing buildings because it needs highly expensive equipments, which are designed for newly built buildings, to install. Therefore, there are numerous limits exist when applying the BEMS in established buildings. The purpose of this study estimates the optimization of RF output power in WSN(Wireless Sensor Networks), which is the essential technology to develop PEMS. The results of this study is as follows ; 1) Applying WSN technique in buildings was possible. 2) As RF output power increases, the number of relay node reduced, therefore, the WSN showed more stability. 3) When estimating optimal RF output power in school, it should be considered between the number of relay node and RF output power. 4) Considering battery consumption and possibility of reception, the best suited RF output power is -20dbm in apartment house.